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Predicting Drug Exposure During Pregnancy Using PBPK Models

Moms want the best for their kids even before they’re born. When I was pregnant with my son and daughter, I watched my diet and tried to stay active. During both of my pregnancies, I had to take medications several times. And I was always concerned about whether the medications could impact my unborn children. Thankfully, my nurse-midwives reassured me that the antibiotic I took for an ear infection or the analgesics I needed for a hand injury were safe to take during pregnancy.

Indeed, the prevalence of medication use among pregnant women is higher than you might think. Most women are prescribed at least one medication during pregnancy. In fact, 50 percent of women take four or more medications during pregnancy. Pregnant women are generally excluded from clinical trials. Thus, while pregnant women are prescribed medications routinely, these medications haven’t been tested in that population. Also, pregnancy is associated with numerous anatomical, biochemical, and physiological changes.

When prescribers lack information about effects of pregnancy on pharmacokinetics, they generally treat pregnant patients with the usual adult dose. If pregnancy causes changes in exposure, that usual dose may result in sub-therapeutic or toxic concentrations depending upon the magnitude and the direction of the change in the pharmacokinetics. In this blog post, I’ll discuss how pregnancy impacts pharmacokinetics and how physiologically-based pharmacokinetic (PBPK) models can predict drug exposure during pregnancy.

Relationship between pharmacokinetics and systemic exposure

The key measurements of systemic exposure are the maximum plasma drug concentration (Cmax) and the area under the drug concentration-time curve (AUC). The trough concentration is sometimes important as well. For oral drugs, the AUC is directly proportional to the dose and bioavailability and inversely proportional to clearance.

So, clearance is what you have to be concerned with regarding pregnancy-induced changes in pharmacokinetics.

Pharmacokinetic changes during pregnancy

Pharmacokinetics quantifies drug ADME (absorption, distribution, metabolism, and excretion). During pregnancy, physiological changes occur that effect ADME. Many of these changes are described in a 2008 Clinical Pharmacology and Therapeutics paper by Hebert and colleagues and a 2016 Clinical Pharmacology and Therapeutics paper by Tasnif and co-authors.

Changes in drug absorption happen during pregnancy that can affect either the rate or extent of absorption. Gastric emptying is delayed, and intestinal motility is reduced. These changes decrease the rate of drug absorption.

Likewise, altered activity of metabolic enzymes in the intestine or liver can impact bio-availability or the extent of absorption. Expression of transporters (OCT2, OAT1, Pgp) in the intestine has also been shown to increase. Increased Pgp levels could reduce bioavailability through enhanced efflux.

Pregnancy also effects drug distribution. Pregnant women gain weight and have increased body fat. They also experience hemodilution; the increase in total body water, plasma volume, and blood volume reduces the blood’s hematocrit. And reduced levels of circulating plasma proteins albumin and α1-acid glycoprotein can increase the fraction of unbound drug. Collectively, these changes tend to increase a drug’s volume of distribution

Protein binding can also affect drug clearance. If the percent unbound of drug in the plasma increases, then more drug is available for clearance.

Pregnancy also alters drug metabolism via several mechanisms. Numerous metabolic enzymes show increased activity during pregnancy including the following cytochrome p450 (CYP) family members: CYP 2C9, 2D6, 2E1, and 3A4. The activity of UGT1A1, which mediates glucuronidation, is also increased. On the other hand, the activity of CYP1A2 decreases during pregnancy.

Also, cardiac output increases in pregnant patients amplifies hepatic blood flow. This physiological change could also augment hepatic clearance, which is particularly important for high extraction ratio drugs.

Finally, pregnancy changes can effect drug excretion primarily in terms of renal clearance. Again, increased cardiac output augments blood flow to the kidneys. Consequently, the glomerular filtration rate is also elevated in pregnant women. In terms of tubular secretion, transporters in the kidney (OCT2, OAT1, and Pgp) are expressed at a higher level during pregnancy, which can also contribute to increased clearance.

All of these changes progress throughout the pregnancy. Thus, pharmacokinetic changes evolve as the pregnancy progresses through the trimesters. Understanding the changes in systemic exposure of a drug during pregnancy is essential to develop evidence-based dosing regimens for pregnant patients.

Lack of information about pregnancy’s impact on PK hinders healthcare

Conducting clinical trials on pregnant patients is generally unfeasible. But, tools are available to inform dosing adjustments. For years, PBPK modeling has been applied to the environmental sciences and toxicology. Over the past decade, this approach has become mainstream in drug development. In particular, PBPK has demonstrated utility in predicting PK changes in special populations like children and pregnant women.

PBPK modeling, in brief

PBPK modeling is a mechanistic-based approach that considers the anatomy and physiology of the human body. It also requires information regarding the medication being studied― its physicochemical properties as well as transporter and drug metabolism information. The general pregnancy PBPK model in the Simcyp Simulator extends upon the 13 compartment whole-body PBPK model by including a fetoplacental unit. The pregnancy PBPK model considers changes in physiological and biochemical parameters as a function of gestational age.

The first step using PBPK to inform changes in PK is to build a model of your drug in virtual healthy subjects. Then you verify the performance of the model against published data of observed Cmax and AUC in healthy subjects. If your model predictions are not close to observed values, you can revise the model to get a better estimate of relevant parameters.

Once you’re confident that you have a good model, you can build the pregnancy PBPK model and perform simulations across different trimesters of pregnancy and compare them to post-partum predictions. Once again, you compare your predictions to published data on your medication in a pregnant population. Model interpretation involves examining physiologic parameters in simulated subjects to identify the main causes of pregnancy-induced changes in exposure.

Supporting optimal dosing for pregnant patients

Women frequently take medications during their pregnancies. These medications aren’t necessarily tested in pregnant women in clinical trials. So prescribers rely on usual adult doses for pregnant patients. Numerous physiological, anatomical, and biochemical changes occur during pregnancy that alter drug disposition. These changes progress as pregnancy progresses. Altered pharmacokinetics can potentially reduce efficacy or cause toxicity in pregnant patients. PBPK pregnancy models can predict pharmacokinetic changes across different trimesters of pregnancy.

Now that my kids are in elementary and pre-school, my “baby days” are behind me. But, I’m glad that these emerging technologies will help guide safer and more effective dosing for pregnant women and support healthier outcomes for moms and babies.

In a recent webinar, Dr. David Taft, Professor at Long Island University’s School of Pharmacy, described how the Simcyp pregnancy-PBPK model was used to predict systemic exposure during pregnancy for two probe medications: tacrolimus and oseltamivir. I hope that you’ll watch the webinar and let me know what you think in the comments section!

About the author

Suzanne Minton
By: Suzanne Minton

Dr. Suzanne Minton is the Director of Content Strategy where she leads a team of writers that develop the whip smart, educational, and persuasive content is the foundation of Certara’s thought leadership programs. She has a decade of experience in corporate marketing and has conducted biomedical research in infectious disease, cancer, pharmacology, and neurobiology. Suzanne earned a BS in biology from Duke University and a doctorate in pharmacology from the University of North Carolina at Chapel Hill.